mirror of https://github.com/JDAI-CV/fast-reid.git
35 lines
975 B
Python
35 lines
975 B
Python
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# encoding: utf-8
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"""
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@author: liaoxingyu
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@contact: sherlockliao01@gmail.com
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"""
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import torch
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import sys
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sys.path.append(".")
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from config import cfg
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from modeling import build_model
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from modeling.bdnet import BDNet
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cfg.MODEL.BACKBONE = 'resnet50'
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cfg.MODEL.WITH_IBN = False
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# cfg.MODEL.PRETRAIN_PATH = '/export/home/lxy/.cache/torch/checkpoints/resnet50_ibn_a.pth.tar'
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net = BDNet('resnet50', 100, 1, False, None, cfg.MODEL.STAGE_WITH_GCB, False)
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y = net(torch.randn(2, 3, 256, 128))
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print(3)
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# net = MGN_P('resnet50', 100, 1, False, None, cfg.MODEL.STAGE_WITH_GCB, cfg.MODEL.PRETRAIN, cfg.MODEL.PRETRAIN_PATH)
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# net = MGN('resnet50', 100, 2, False,None, cfg.MODEL.STAGE_WITH_GCB, cfg.MODEL.PRETRAIN, cfg.MODEL.PRETRAIN_PATH)
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# net.eval()
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# net = net.cuda()
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# x = torch.randn(10, 3, 256, 128)
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# y = net(x)
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# net = osnet_x1_0(False)
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# net(torch.randn(1, 3, 256, 128))
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# from ipdb import set_trace; set_trace()
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# label = torch.ones(10).long().cuda()
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# y = net(x, label)
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